CN111815769B - Modeling method, computing device and storage medium for thrust covered zone construction - Google Patents
Modeling method, computing device and storage medium for thrust covered zone construction Download PDFInfo
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Abstract
The embodiment of the application discloses a modeling method, a modeling device, computing equipment and a storage medium for a reverse-thrust cladding structure belt structure, belonging to the technical field of computers, wherein the method comprises the following steps: according to the form data reflecting the form and geographical position distribution of each stratum of the structure of the thrust-covered structural band and a two-dimensional acoustic wave equation, a target structural model is established, forward modeling is conducted on the target structural model to obtain a target quantity version, spread analysis is conducted on faults of at least two different orders according to the target quantity version, a first layer grid model is established, the first layer grid model is optimized according to a target multi-layer difference value algorithm to obtain a second layer grid model, the problem that the three-dimensional model established by the corner grid method deforms at the fault part of the thrust-covered structural band and cannot truly reflect the three-dimensional structure of the thrust-covered structural band can be solved, and accuracy of the three-dimensional model for reflecting the thrust-covered structural band is improved.
Description
Technical Field
The embodiment of the application relates to the field of oil and gas field development in petroleum industry, in particular to a modeling method, computing equipment and storage medium for a reverse thrust cladding structural belt structure.
Background
In the geological exploration of the petroleum industry, technicians typically employ modeling methods to interpret geologic structures. Meanwhile, modeling is also an important means for three-dimensional reconstruction of geologic structures.
In the field of hydrocarbon reservoir exploration and production, thrust cladding bands are advantageous formations for storing hydrocarbons. Thus, three-dimensional reconstruction of the thrust covered zone is a necessary preparation for recovery of the hydrocarbon reservoir in the thrust covered zone. In some techniques, technicians model the thrust cladding bands using a corner grid approach.
However, the three-dimensional model established by the corner grid method is deformed at the fault portion of the thrust cladding structural band, and cannot truly reflect the three-dimensional structure of the thrust cladding structural band.
Disclosure of Invention
The embodiment of the application provides a modeling method, a modeling device, a computing device and a storage medium for a reverse-flow coating structure belt structure, which can solve the problem that a three-dimensional model established by a corner grid method deforms at a fault part of the reverse-flow coating structure belt and cannot truly reflect the three-dimensional structure of the reverse-flow coating structure belt. The technical scheme is as follows:
According to an aspect of the present application, there is provided a modeling method of a thrust cladding band configuration, the method comprising:
Establishing a target construction model according to morphology data and a two-dimensional acoustic wave equation, wherein the morphology data are used for indicating morphology and geographical position distribution of each stratum of the thrust cladding construction band construction;
developing forward modeling on the target construction model to obtain a target quantity version, wherein the target quantity version comprises at least two types of block construction styles which are indicated and amplified n times, and n is greater than 1;
According to the target volume version, performing spread analysis on at least two faults with different sequence levels, and establishing a first layer grid model;
And optimizing the first layer grid model according to a target multi-layer difference algorithm, and establishing a second layer grid model, wherein the second layer grid model has higher precision than the first layer grid model, and is a three-dimensional model of the thrust cladding structure belt structure.
According to another aspect of the present application, there is provided a modeling apparatus for reverse-pushing a build belt construction, the apparatus comprising:
The first modeling module is used for building a target construction model according to morphological data and a two-dimensional acoustic wave equation, wherein the morphological data is used for indicating morphology and geographical position distribution of each stratum of the thrust cladding construction band construction;
the quantitative version acquisition module is used for developing forward modeling on the target construction model to acquire a target quantitative version, wherein the target quantitative version comprises at least two types of block construction patterns which are amplified n times, and n is greater than 1;
the second modeling module is used for performing spread analysis on at least two faults with different sequence levels according to the target measuring edition, and establishing a first layer grid model;
And the third modeling module is used for optimizing the first layer grid model according to a target multi-layer difference value algorithm, and establishing a second layer grid model, wherein the second layer grid model has higher precision than the first layer grid model, and is a three-dimensional model of the thrust cladding structure belt structure.
According to another aspect of the present application, there is provided a computing device comprising a processor and a memory having stored therein at least one instruction that is loaded and executed by the processor to implement a modeling method of a thrust covered zone construction as provided by an implementation of the present application.
According to another aspect of the present application, there is provided a computer readable storage medium having stored therein at least one instruction that is loaded and executed by a processor to implement a modeling method of a thrust covered zone configuration as provided by an implementation of the present application.
The technical scheme provided by the embodiment of the application has the beneficial effects that:
And establishing a target construction model according to the morphological data and the two-dimensional acoustic wave equation, wherein the morphological data are used for indicating the morphological and geographical position distribution of each stratum of the thrust-covered construction zone structure, forward modeling is carried out on the target construction model, a target quantity version is obtained, the target quantity version comprises fault block construction patterns which indicate at least two types and are amplified by n times, according to the target quantity version, spread analysis is carried out on faults of at least two different sequence levels, a first layer grid model is established, the first layer grid model is optimized according to a target multi-layer difference algorithm, a second grid model is established, the accuracy of the second layer grid model is higher than that of the first layer grid model, and the second layer grid model is a three-dimensional model of the thrust-covered construction zone structure. According to the application, the forward modeling of the target construction model can be utilized to obtain the target quantity version, and on the basis, faults of different sequence levels are subjected to spread analysis to obtain the first layer grid model, and then the first layer grid model is optimized to obtain the second layer grid model.
Drawings
In order to more clearly describe the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments of the present application will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a block diagram of a computing device provided by an exemplary embodiment of the present application;
FIG. 2 is a flow chart of a modeling method of a thrust covered zone configuration provided by an exemplary embodiment of the application;
FIG. 3 is a flow chart of a modeling method for a thrust covered zone configuration provided by another exemplary embodiment of the application;
FIG. 4 is a schematic diagram of an implementation of a three-dimensional modeling technique for a complex push construction provided by an embodiment of the present application;
FIG. 5 is a cross-sectional view of a deposited microphase model of the zone of construction in which a C gas reservoir is located, provided by the present application;
FIG. 6 is a 2D acoustic wave equation forward modeling Y-shaped fault template provided by the present application;
FIG. 7 is a feature map of the type of construction in a three-dimensional region of a thrust covered construction area provided by the present application;
FIG. 8 is a deep conversion seismic profile view of a complex structure with line1528 lines with different fault levels and combination relations;
FIG. 9 is a schematic diagram of a complex structure reflected by a thrust complex structure belt unstructured grid modeling technique provided by an embodiment of the present application;
FIG. 10 is a diagram of a grid distribution of different low-order fault planes provided by an embodiment of the present application;
FIG. 11 is a graph of minimum vertical thickness contrast for a single well determined by a convolution difference algorithm provided by an embodiment of the present application;
FIG. 12 is a graph of an algorithmic simulated adaptation analysis in a thrust covered architecture layer provided by an embodiment of the application;
FIG. 13 is a three-dimensional structural model of a complex thrust cladding strip provided by an embodiment of the present application;
FIG. 14 is a block diagram of a modeling apparatus for a thrust runner configuration according to an exemplary embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings.
When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
In the description of the present application, it should be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "connected," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art. Furthermore, in the description of the present application, unless otherwise indicated, "a plurality" means two or more. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship.
In the embodiment of the application, the structural modeling is a necessary process and means for structural interpretation and three-dimensional geological modeling commonly used in the petroleum geological industry. In the construction modeling, main technical means comprise geological measurement and control means, seismic measurement means, drilling sampling means and the like. The original address data can be acquired by the technicians through the various technical means, and then behavior structure description and fault prediction such as horizon tracking, ant tracking and three-dimensional address modeling software are utilized to finally provide a three-dimensional structure model for drilling implementation and oil and gas reservoir recognition.
Typically, the present construction modeling techniques are directed to gas reservoir applications where the characteristics of the formation are smooth and fracture development are clear. The construction modeling technology aiming at complex thrust coverage is in a technology attack stage, and no mature scheme in the industry can refer to reference.
In view of the modeling method of the thrust covered structure belt structure, the computing equipment can develop fine three-dimensional structure modeling work for the carbonate rock reef beach gas reservoir of the thrust covered structure, establish a high-precision three-dimensional structure model which is relatively close to the underground real condition, finely characterize the strong heterogeneity characteristic of the gas reservoir, and simultaneously be beneficial to developing the later gas reservoir numerical simulation research and providing technical support for the reserve evaluation and subsequent development of the gas reservoir.
In addition, the modeling method of the thrust cladding structure belt structure provided by the embodiment of the application can be used in the three-dimensional modeling process of a carbonate gas reservoir, and can effectively solve the problems that the complex thrust cladding structure gas reservoir is complex in fracture, multiple in broken blocks and the like and is difficult to characterize in the three-dimensional structure modeling.
The modeling method of the reverse-push tectorial belt structure, which is shown in the embodiment of the application, can be applied to a computing device, wherein the computing device is provided with a display screen and has a modeling function of the reverse-push tectorial belt structure. Computing devices may include desktop computers, all-in-one computers, servers, workstations, supercomputers, and the like.
Referring to fig. 1, fig. 1 is a block diagram of a computing device according to an exemplary embodiment of the present application, where the computing device includes a processor 120 and a memory 140, and at least one instruction is stored in the memory 140, and the instruction is loaded and executed by the processor 120 to implement a modeling method for a thrust covered zone configuration according to various method embodiments of the present application.
In the present application, the computing device 100 is an electronic device having a mass data processing function. When the computing device 100 runs the data analysis software, the computing device 100 is capable of building a target formation model from morphology data indicative of morphology and geographical location distribution of each formation of the thrust cladding formation belt formation and the two-dimensional acoustic wave equation; developing forward modeling on the target construction model to obtain a target quantity version, wherein the target quantity version comprises at least two types of block construction styles which are indicated and amplified n times, and n is greater than 1; according to the target volume version, performing spread analysis on at least two faults with different sequence levels, and establishing a first layer grid model; and optimizing the first layer grid model according to a target multi-layer difference algorithm, and establishing a second layer grid model, wherein the second layer grid model has higher precision than the first layer grid model, and is a three-dimensional model of the thrust cladding structure belt structure.
Processor 120 may include one or more processing cores. The processor 120 utilizes various interfaces and lines to connect various portions of the overall computing device 100, perform various functions of the computing device 100, and process data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 140, and invoking data stored in the memory 140. Alternatively, the processor 120 may be implemented in at least one hardware form of digital signal Processing (DIGITAL SIGNAL Processing, DSP), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 120 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), and a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 120 and may be implemented by a single chip.
Memory 140 may include random access Memory (Random Access Memory, RAM) or Read-Only Memory (ROM). Optionally, the memory 140 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 140 may be used to store instructions, programs, code sets, or instruction sets. The memory 140 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described below, etc.; the storage data area may store data and the like referred to in the following respective method embodiments.
Referring to fig. 2, fig. 2 is a flow chart of a modeling method of a thrust covered zone configuration provided by an exemplary embodiment of the present application. The modeling method of the thrust covered zone configuration may be applied in the computing device shown above. In fig. 2, the modeling method of the thrust cladding band configuration includes:
At step 210, a target formation model is created from morphology data indicative of morphology and geographical location distribution of each formation of the thrust cladding formation band configuration and the two-dimensional acoustic wave equation.
In an embodiment of the present application, the computing device may be an electronic device capable of mass data processing. For example, supercomputers and large computing devices are capable of processing massive amounts of data acquired in the field of geological exploration.
In an embodiment of the application, the computing device is capable of acquiring morphological data. The morphology data is used to indicate morphology and geographic location distribution of each formation of the thrust cladding zone formations. In one possible implementation, the morphology data includes at least one of seismic data, drilling information data, and logging data. It should be noted that the drilling information data may be implemented as core data. In one practical scenario, core data, seismic data, and logging data are data that are independent sources of each other. The computing equipment can collect the morphological data to form a basic research database.
Optionally, in one possible implementation, the morphological data further comprises historical geological data.
Optionally, in one possible implementation, the morphological data further includes production dynamics data.
In an embodiment of the application, the computing device will build a target construction model from the morphology data in combination with a two-dimensional acoustic wave equation.
Step 220, forward modeling is performed on the target construction model, and a target scale is obtained, wherein the target scale comprises a broken block construction pattern which indicates at least two types and is amplified n times, and n is larger than 1.
In an embodiment of the application, the computing device will develop a forward modeling of the target construction model, obtaining a target quantitative version comprising at least two types of block construction styles that are n times amplified, n being greater than 1.
In addition, forward modeling is also called geophysical forward modeling (English: geophyrsical forward calculation), which refers to a process of calculating field anomalies or effects caused by a geologic body from the occurrence state and physical parameters of the geologic body in the geophysical data interpretation theory. The occurrence state of the geologic body comprises at least one of shape, occurrence and space position, and the physical parameters comprise at least one of density, magnetism, electricity, elasticity and speed.
Alternatively, the occurrence and physical properties of a known geologic body may be collectively referred to as a model.
Alternatively, the target volume version is an idealized template obtained through forward modeling, which is used to guide the actual tomographic interpretation.
And 230, performing spread analysis on at least two faults with different sequence levels according to the target scale, and establishing a first layer grid model.
In the embodiment of the application, the computing equipment can perform spread analysis on at least two faults with different sequence levels, and establish a first layer grid model.
Optionally, the computing device is capable of performing different order level fault spread analysis, determining the size and orientation of the planar grid, and establishing a high-precision layer grid model, that is, establishing a first layer grid model, by using a non-structural grid method (English: delaunay) modeling technology and a wavelet decomposition technology on the basis of determining the fault influence limit and the fault scale.
The planar mesh size and orientation are parameters required for establishing the first layer mesh model. Unstructured grid modeling techniques and wavelet decomposition techniques are algorithms used for modeling. The fault impact limits and fault scale are geologic model data. When the computing device acquires the parameters, algorithms, and geologic model data simultaneously, the computing device is able to build a first-level mesh model.
Step 240, optimizing the first layer grid model according to the target multi-layer difference algorithm, and establishing a second layer grid model, wherein the second layer grid model has higher precision than the first layer grid model, and is a three-dimensional model with a back-punching cladding structure.
In the embodiment of the application, the computing equipment can optimize the first layer grid model according to the target multi-layer difference value algorithm and establish the second layer grid model. It should be noted that the target multi-layer face difference algorithm is used to improve the accuracy of the face mesh model. The second layer grid model is higher in precision than the first layer grid model, and is a three-dimensional model with a structure of a thrust cladding structure band.
In summary, in the modeling method of the structure of the thrust-covered structural band provided in this embodiment, a target structural model is established according to the morphological data and the two-dimensional acoustic wave equation, where the morphological data is used to indicate the morphology and the geographical position distribution of each stratum of the structure of the thrust-covered structural band, forward modeling is performed on the target structural model, a target quantity version is obtained, the target quantity version includes a fault block structural style indicating at least two types and amplified n times, according to the target quantity version, spread analysis is performed on faults of at least two different order levels, a first layer mesh model is established, the first layer mesh model is optimized according to a target multi-layer difference algorithm, a second layer mesh model is established, the accuracy of the second layer mesh model is higher than that of the first layer mesh model, and the second layer mesh model is a three-dimensional model of the structure of the thrust-covered structural band. According to the application, the forward modeling of the target construction model can be utilized to obtain the target quantity version, and on the basis, faults of different sequence levels are subjected to spread analysis to obtain the first layer grid model, and then the first layer grid model is optimized to obtain the second layer grid model.
Based on the solution disclosed in the previous embodiment, the computing device is further capable of acquiring target survey data prior to model establishment, acquiring morphology data of the thrust runner belt structure by analyzing the target survey data, and using the intermediate-level mesh model as a transition for generating the model when the second-level mesh model is established, improving accuracy of the thrust runner belt structure three-dimensional model. For details, please refer to the following examples.
Referring to fig. 3, fig. 3 is a flowchart of a modeling method for a thrust covered zone configuration according to another exemplary embodiment of the present application. The modeling method of the thrust covered zone configuration may be applied in the computing device shown above. In fig. 3, the modeling method of the thrust cladding band configuration includes:
at step 310, target survey data is acquired, the target survey data being geological data indicative of the thrust runner formations collected while being surveyed.
In an embodiment of the application, the computing device is capable of acquiring target survey data, which is geological data collected by a worker while conducting a survey for a thrust covered zone configuration. The computing device may obtain the target survey data by manual input or disk copying, etc.
In one possible implementation, the computing device is further capable of acquiring target survey data by acquiring single well data for a target single well, the target single well being a single well in a thrust cladding zone.
It should be noted that the single well data may include at least one of logging data, well point stratification data, and microphase data. Optionally, the present embodiment may also correct the single well data when acquiring the single well data of the target single well. The correction operation comprises singular value taking, core correction and the like.
Step 320, analyzing the target survey data to obtain morphology data of the thrust covered zone configuration.
In the embodiment of the application, the computing equipment can analyze target exploration data through a three-dimensional earthquake and well fine calibration technology and acquire the morphological data of the thrust cladding structure belt structure.
In one possible implementation, the computing device is further capable of processing the single well data via a wavelet decomposition technique to obtain morphology data of the thrust covered zone, wherein the morphology data includes gas reservoir geodetic data, and fault parameters of the target single well.
And 330, establishing a target construction model according to the morphological data and the two-dimensional acoustic wave equation.
The execution of step 330 is the same as that of step 210, and will not be described in detail here.
And step 340, forward modeling is performed on the target construction model, and the target scale is obtained.
The execution of step 340 is the same as that of step 220 and will not be described in detail here.
Step 350, determining fault influence limits and fault scales of the thrust cladding zone configuration according to the target magnitude version.
In an embodiment of the application, the computing device is capable of determining fault impact limits and fault scales for the thrust covered zone configuration from the target magnitude version. It should be noted that this operation may be quantitative analysis in the geologic model parameters.
And 360, performing spread analysis on the faults of at least two different sequence levels according to the fault influence limit and the fault scale, and establishing a first layer grid model.
In the embodiment of the application, the computing equipment can utilize the modeling technology of the unstructured network method (English: delaunay) and the wavelet decomposition technology to develop fault spread analysis of different order levels on the basis of fault influence limit and fault scale.
And step 370, optimizing the first layer grid model according to the target multi-layer difference algorithm to obtain an intermediate layer grid model.
In the embodiment of the application, the computing device can also determine a target multi-level difference algorithm from the candidate multi-level difference algorithms. The candidate multi-level difference algorithm comprises at least two algorithms of a kriging algorithm, a minimum curvature method and a convergence method.
Step 380, well layering data interpolation is carried out on the middle layer mesh model, and a second layer mesh model is obtained.
In the embodiment of the application, the computing equipment carries out well layering data interpolation on the middle surface grid model, optimizes the geological fault cutting relation, establishes the effective contact relation between the surface and the fault, and thus constructs a more complex and accurate fault model.
In summary, according to the modeling method for the thrust-covered structural band structure provided by the application, the forward modeling of the target structural model can be utilized to obtain the target scale, on the basis, faults of different sequence levels are subjected to spread analysis to obtain the first layer grid model, and then the first layer grid model is optimized to obtain the second layer grid model.
As another implementation manner of the present application, the present application provides an execution procedure that may be applied in a computing device as shown in fig. 1, where the procedure includes the following steps:
The application can build an integrated model by adopting an unstructured grid algorithm to form a complex push-cover structure three-dimensional structure modeling method taking 'model forward and reverse, combined quantitative analysis and unstructured grid building' as a core.
And (1) collecting gas reservoir seismic data, drilling information data, logging data, production dynamic data and geological background related data, and performing rule analysis, identification and division on the structural zones of the complex thrust structural zones by using a three-dimensional seismic and well fine calibration technology.
And (2) establishing a construction model by using the data such as the construction band dividing result, fault occurrence, construction stress analysis parameters and the like in the step (1) and adopting a 2D acoustic wave equation to develop forward modeling, and finally forming quantitative versions of the amplification factors of different types of fault block construction styles.
And (3) carrying out quantitative division of fault levels on the basis of the scale of the magnification of the different types of fault block construction patterns built in the step (2), and determining fault influence limits and fault scales.
And (4) on the basis of determining fault influence limit and fault scale in the step (3), carrying out fault spread analysis of different order levels by using a non-structural grid method (delaunay) modeling technology and a wavelet decomposition technology, determining the size and the direction of a plane grid, and establishing a high-precision layer grid model.
And (5) developing the optimization of the kriging algorithm, the minimum curvature method and the convergence method multi-layer difference value algorithm on the basis of the high-precision layer grid model established in the step (4), and establishing the layer grid model by the final optimization convergence method.
And (6) carrying out well layering data interpolation, optimizing fault cutting relation, establishing effective contact relation between a layer and a fault and constructing a more accurate complex fault model on the basis of the layer grid model in the step (5).
According to the three-dimensional structure modeling method formed by the steps (1) to (6), the complex pushing structure three-dimensional structure modeling technology taking 'model forward inversion, combined quantitative analysis and unstructured grid establishment' as a core can be used, the working limit of structure interpretation and geological modeling is highlighted, and a complex structure body is taken as a research unit. The conventional plane grid parameter selection uses the computing capability of a computer as a standard, the application proves that the modeling of the complex structural band structure needs to fully consider the fault combination relation and the fault influence limit, and the definite lowest order fault limit has obvious control function on the size and the azimuth of the complex structural band plane grid, so that the application provides a principle of using 'different order fault combination analysis' as the determination of the plane grid parameter. The size and the azimuth of the plane model grid provided by the method are controlled by the lowest order fault, and a technical foundation for modeling the complex structural belt structure is laid.
Optionally, the three-dimensional structural modeling method of the complex thrust cladding structure provided by the application starts from earthquake and single well data, and combines the structure forward and backward exercise technology to finely engrave the structural model by using an unstructured grid modeling method, so that the precision of the structural model is improved.
Optionally, the application promotes the technical development of the geological modeling of the complex reverse-flushing structure by applying parameters such as plane grid azimuth, size, plane difference algorithm optimization and the like which are easily ignored in the conventional three-dimensional structure modeling and executing operation.
As another implementation manner of the present application, the present application also provides the following application scenario. Referring to fig. 4, fig. 4 is a schematic diagram illustrating implementation of a three-dimensional modeling technique for a complex push-up structure according to an embodiment of the present application. In fig. 4, the data sources of the base research database 400 may include core data 411, log data 412, seismic data 413, and historical data 414. It should be noted that the history data 414 may also be referred to as previous achievements.
In fig. 4, the computing device is capable of extracting data from the underlying research database 400 for analysis in accordance with three flows of complex structural band structural style, fault fine-division, and cause analysis techniques, respectively.
In the complex construction tape construction pattern flow, four steps of construction pattern 42a1, model forward 42a2, construction morphology 42a3 and construction classification 42a4 are included.
In the tomographic fine division flow, four steps of tomographic division 42b1, period identification 42b2, combination pattern 42b3, and fracture level 42b4 are included.
The process of the cause analysis technique includes four steps of cause analysis 42c1, combination pattern 42c2, stress analysis 42c3, and comprehensive analysis 42c 4.
After the data in the basic research database 400 is processed by the above three processes of complex structural band structural style, fault fine division and cause analysis technology, the data can be processed by the following processing steps of geologic model parameters, which are respectively:
And step 430, performing quantitative analysis on the geologic model parameters.
Step 440, extracting the non-structural grid method grid model through fault treatment.
And 450, constructing a corner network construction model.
Step 460, build a complex construction model.
In summary, in the embodiment provided by the application, by using the method of modeling the three-dimensional structure of the complex push-cover structure taking the model forward-inversion, the combined quantitative analysis and the unstructured grid establishment as the core, the plane distribution trend and the vertical distribution trend of different trap types caused by different structural stresses of the complex push-cover structure can be more accurately represented, the three-dimensional visualization can be realized, the accuracy of structure recognition is improved, and the foundation is laid for the well position deployment and the later development work of the gas reservoir.
In another modeling approach to thrust cladding a structural band construct, the present embodiment provides a solution that can overcome: the construction modeling method can not fully characterize the space spread characteristic and the trap characteristic of the thrust cladding construction under the sparse mesh well condition. The C gas reservoir is taken as an example for introduction, wherein the C gas reservoir has complex structure combination, larger fault scale and different fault scales which are mutually interwoven, and is a complex fracture system. The whole folds are strong in deformation and complex in fracture, and a series of folds which are distributed in northeast, southwest and west directions and are nearly parallel are formed into a broken high-structure group. In this configuration, 8 local high points develop. Optionally, the trap area of the C gas reservoir can reach 41.12 square kilometers, and the faults have 47 faults; the structural development fault type is mainly reverse fault, the fault patterns are numerous, and the fault distance is in the interval of 125m to 635 m.
And (1) acquiring well information data, single well logging data, well point layering data and microphase data of a single well, correcting all the single well data, completing works such as singular value taking, core correction and the like, and determining stratum and fault parameters of a C gas reservoir.
Step (2) utilizing the well information data, the single well logging data and the well point layering data in the step (1) to perform regular analysis and identification division on a structural zone where the C gas reservoir is located by using a three-dimensional earthquake and well fine calibration technology, and determining that the structural occurrence is north east, near east west and near south north; the structural zone is divided into a C1 thrust covered zone, a C2 hidden leading edge zone and a C3 depression zone from west to east in sequence. The development of multiple latent structures or latent blocks and noses sealed in faults still shows the characteristic of low north west high south east.
Referring to fig. 5, fig. 5 is a cross-sectional view of a deposition microphase model of a structural zone in which a C gas reservoir is located according to the present application. In fig. 5, 510 is the C1 thrust coverage zone, 520 is the C2 blind leading edge zone, and 530 is the C3 depression zone.
And (3) based on the step (1), adopting forward and backward mutual introduction ideas, adopting a 2D acoustic wave equation to establish a structural model to develop forward modeling, forming quantitative versions of the amplification factors of different types of fault block structural styles, developing fault block structural style research, and guiding structural interpretation analysis of the complex thrust structural belt. Based on relatively fine and reliable construction explanation, the construction background types of the construction band are divided into five types and quantitatively evaluated (bump anticline, rolling anticline, nose breaking structure, ascending breaking block and descending breaking block) by combining with the construction stress simulation analysis research of the zone, so as to guide the establishment of a subsequent construction model.
Referring to fig. 6, fig. 6 is a 2D acoustic wave equation forward modeling Y-fault template provided by the present application. Wherein the interface 610 represents a grid 10 x 10, a dominant frequency 40Hz forward model. Interface 620 represents grid 10 x 10, a dominant frequency 40Hz forward cross-section. Interface 630 represents a Y-type tomographic template.
Referring to fig. 7, fig. 7 is a feature diagram of a three-dimensional region internal structure type of a thrust covered region according to the present application. In fig. 7, typical patterns, construction traps, and seismic profiles of several construction types are disclosed for bump anticline, roll anticline, nose break, rise break, and fall break.
And (4) carrying out fine analysis on the fault combination relation on the basis that the structural background types of the structural band in the step 3) are divided into five types and quantitatively evaluated, and determining the plane combination style and the section combination style of the fault in the complex structural band. Determining four fault combined patterns (a plurality of groups of Y-shaped, ladder-shaped, cutting-shaped and barrier-shaped) of complex structural zone development, and three-stage fault modes: the primary fracture controls the development boundary of the broken block, the secondary fracture control area stretches, and the tertiary fracture leads to the complication of the broken block.
And (5) determining the plane distribution characteristics and influence boundaries of faults of different sequence levels on the basis of quantitative evaluation and fault pattern analysis constructed in the step (4). The fracture combination relation of the high-order level faults (primary and secondary) is clear, the break points are clear, the construction model mainly adopts primary and secondary constructions, and the fault cutting and grid connection are controlled. The low-order level faults (three levels) are regional stress release products, are positioned at the tail ends of the high-order level faults, have complex fault combination relations and break points, and are derivative faults.
Referring to fig. 8, fig. 8 is a deep conversion seismic section view of a complex structure with line1528 line with different fault levels and combination relations. Wherein, the breakpoints of the high-order fault 810 and the high-order fault 820 are clear; the break point of the low order level fault 830 is complex.
And on the basis of clear analysis of the construction trap types, carrying out construction modeling research. Through technical comparison, an unstructured grid algorithm is adopted to determine plane grid division parameters. Optionally, the grid scale on the plane uses the lowest order fault concentrated development area to set 1-2 grids as the lower limit. Optionally, the lowest order fault spacing of the complex flip structure is 55 meters, and the lower limit of the planar grid is determined to be 30 meters.
The longitudinal division precision utilizes wavelet decomposition technology to build high-precision layer sequence stratum grillage. And (3) integrating a prediction error filtering analysis technology to determine that the longitudinal grid division layer sequence is 2 four-level layer sequences and 4 small layers. And combining with the development positions of the reservoir, longitudinally dividing the modeling structure into 4 zones, wherein the reservoir is mainly distributed in 1 and 2. The target component was divided into 8 five-order sequences using the d3 curve of wavelet decomposition. And combining the minimum difference thickness of the gyrations to determine the minimum dimension of the longitudinal grid of 0.82m.
Referring to fig. 9, fig. 9 is a schematic diagram of a complex structure reflection of the unstructured grid modeling technique for a complex structure of a thrust complex structure provided by an embodiment of the present application. Where interface 910 represents a schematic of a corner grid and interface 920 represents a schematic of a non-structured grid.
Referring to fig. 10, fig. 10 is a diagram illustrating a grid distribution diagram of a fault plane with different low order levels according to an embodiment of the present application.
Referring to fig. 11, fig. 11 is a graph showing a comparison of minimum vertical thickness of a single well determined by a convolution difference algorithm according to an embodiment of the present application. Wherein interface 1110 is used to indicate a graphical representation of the minimum differential roll-back thickness of 0.69 meters, roll-down depth (7452.70-7453.39). Interface 1120 is used to indicate a graphical representation of the minimum difference in rotational sag thickness of 1.16 meters, and the sag depth (7216.98-7218.14). Interface 1130 is used to indicate a graphical representation of the minimum difference in rotational sag thickness of 0.61 meters, and the sag depth (7160.84-7161.45).
And (3) developing a kriging algorithm, a minimum curvature method and a convergence method to optimize a multi-layer face difference algorithm, and finally optimizing the convergence method to establish a face grid model. The methods such as the Kriging algorithm, the minimum curvature method, the convergence method and the like have certain differences in precision due to different algorithms, and the differences can be basically ignored in the conventional three-dimensional geological modeling. The present application finds that some algorithms are not applicable in complex, thrust covered constructions. In the application process of the kriging algorithm, the change of the interwell difference value is gentle, but the simulation of a structural surface, particularly a complex structural part of the thrust, has serious deformation of the surface, and the structural characteristics cannot be accurately described basically. Through comparison, the kriging algorithm, the minimum curvature method and the convergence method selected finally are preferably selected, and the difference between the kriging algorithm and the minimum curvature method reaches 7.77 meters.
Referring to fig. 12, fig. 12 is a graph showing an algorithm simulated adaptability analysis in a thrust overlay architecture layer according to an embodiment of the present application. Wherein graph 1210 represents a kriging algorithm for indicating that the interwell difference varies relatively smoothly and simulating a face side lift. Plot 1220 shows a minimum curvature method for indicating that the interwell difference changes relatively smoothly. Plot 1230 represents a convergence method to indicate that the risk of interwell simulation is minimized.
And constructing a more accurate complex fault model by utilizing a three-dimensional gridding (English: PILLAR GRIDDING) construction modeling technology. And controlling the closure of the cross-cut fault, the reverse fault and the spade fault section and the extinction point of the fault point, optimizing the fault cutting relationship, and establishing the effective contact relationship between the layer surface and the fault.
Building a construction model: according to the established layer model and zone model, the input well point, fault line and other data are cut off and transformed, singular values are removed, the combination relation of each structure is obtained by layering and layering, and finally a relatively accurate reverse-flushing complex structure model is established.
Model verification: as can be seen from the established complex thrust structural model, D1 is configured as a rising break block type structure, D2 is configured as a bump anticline type structure, and D3 is configured as a rolling anticline type structure.
The drilling data prove that the D1 structure and the D2 structure are actually non-communicated structural units, and the two structures have obvious differences in crack development degree due to different structural stress and fault combination modes. The D1 structure is subjected to bidirectional extrusion, fracture development, and the test yield of the test gas well is more than 80 square; d2 bulge anticline structure, obvious fault sliding characteristic, serious stress release, less fracture development and gas well test yield of only 30 square. Therefore, the established reverse-flushing complex structural belt structural model has credibility and can be used for guiding trap evaluation and subsequent development of the gas reservoir.
Referring to fig. 13, fig. 13 is a three-dimensional model of a complex thrust covered zone according to an embodiment of the present application.
The following are examples of the apparatus of the present application that may be used to perform the method embodiments of the present application. For details not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the method of the present application.
Referring to fig. 14, fig. 14 is a block diagram showing a modeling apparatus of a thrust cladding band configuration according to an exemplary embodiment of the present application. The modeling means of the thrust covered zone configuration may be implemented as all or part of a computing device by software, hardware, or a combination of both. The device comprises:
a first modeling module 1410 for building a target formation model from morphology data and a two-dimensional acoustic wave equation, the morphology data being indicative of morphology and geographic location distribution of each formation of a thrust cladding formation zone formation;
the quantitative version obtaining module 1420 is used for developing forward modeling on the target construction model to obtain a target quantitative version, wherein the target quantitative version comprises at least two types of block construction patterns which are amplified n times, and n is greater than 1;
The second modeling module 1430 is configured to perform a spreading analysis on at least two faults of different order levels according to the target scale, and establish a first layer grid model;
And the third modeling module 1440 is configured to optimize the first layer mesh model according to a target multi-layer difference algorithm, and build a second layer mesh model, where the second layer mesh model has a higher accuracy than the first layer mesh model, and the second layer mesh model is a three-dimensional model of the thrust cladding band structure.
In an alternative embodiment, the apparatus further comprises a survey data acquisition module and a survey data analysis module. An exploration data acquisition module for acquiring target exploration data, the target exploration data being geological data indicative of a collection of the thrust cladding zone formations when surveyed; and the exploration data analysis module is used for analyzing the target exploration data and acquiring the morphological data of the thrust-covered structural band structure.
In an alternative embodiment, the survey data analysis module is configured to analyze the target survey data via three-dimensional seismic and well fine calibration techniques to obtain morphology data of the thrust covered zone formations.
In an alternative embodiment, the survey data acquisition module is configured to acquire single well data for a target single well, the target single well being a single well in a thrust coverage zone. The exploration data analysis module is used for processing the single well data through a wavelet decomposition technology and obtaining the morphological data of the thrust cladding structural band, wherein the morphological data comprise gas reservoir ground data and fault parameters of the target single well.
In an alternative embodiment, the second modeling module 1430 is configured to determine fault impact limits and fault scales for the thrust covered zone configuration based on the target metrology plate; and performing spread analysis on at least two faults with different sequence levels according to the fault influence limit and the fault scale, and establishing the first layer grid model.
In an alternative embodiment, the third modeling module 1440 is configured to optimize the first level mesh model according to a target multi-level difference algorithm to obtain an intermediate level mesh model; and carrying out well layering data interpolation on the middle layer grid model to obtain the second layer grid model.
In an alternative embodiment, the apparatus further comprises a screening module configured to determine a target multi-level difference algorithm from candidate multi-level difference algorithms, the candidate multi-level difference algorithms including at least two of a kriging algorithm, a minimum curvature method, and a convergence method.
Embodiments of the present application also provide a computer readable medium storing at least one instruction for loading and executing by the processor to implement the modeling method of a thrust covered zone configuration as described in the various embodiments above.
It should be noted that: the modeling apparatus of the structure of the thrust covered belt provided in the above embodiment is only exemplified by the above-described division of the functional modules when performing the modeling method of the structure of the thrust covered belt, and in practical applications, the above-described functional distribution may be performed by different functional modules, i.e., the internal structure of the device is divided into different functional modules, as needed, to perform all or part of the functions described above. In addition, the modeling apparatus of the structure of the thrust cladding band provided in the above embodiment and the modeling method embodiment of the structure of the thrust cladding band belong to the same concept, and detailed implementation processes thereof are referred to method embodiments, and are not repeated here.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
The above embodiments are merely exemplary embodiments of the present application and are not intended to limit the present application, and any modifications, equivalent substitutions, improvements, etc. that fall within the spirit and principles of the present application should be included in the scope of the present application.
Claims (9)
1. A method of modeling a thrust cladding strip configuration, the method comprising:
Establishing a target construction model according to morphology data and a two-dimensional acoustic wave equation, wherein the morphology data are used for indicating morphology and geographical position distribution of each stratum of the thrust cladding construction band construction;
developing forward modeling on the target construction model to obtain a target quantity version, wherein the target quantity version comprises at least two types of block construction styles which are indicated and amplified n times, and n is greater than 1;
Quantitatively dividing the fault level of the target measuring plate, and determining the fault combination relation of the thrust cladding structural band;
analyzing the fault combination relation, and determining a section combination pattern of a fault in a complex structure band and a three-level fault mode, wherein the three-level fault mode comprises primary fracture, secondary fracture and three-level fracture, the primary fracture controls the development boundary of a fault block, the secondary fracture control area stretches, and the three-level fracture controls the complexity of the fault block;
Determining plane distribution characteristics and influence boundaries of faults of at least two different sequence levels according to the section combination patterns and the three-level fault modes, wherein the at least two different sequence levels comprise high-order faults including the primary fracture and the secondary fracture and low-order faults including the three-level fracture, the low-order faults are positioned at the tail ends of the high-order faults, the low-order faults are derivative faults, and the fault cuts and the connection of a plane grid are controlled by the high-order faults;
determining dividing parameters of the plane grid by using an unstructured grid modeling technology according to the plane distribution characteristics and the influence boundary, wherein the scale of the plane grid takes a fault concentrated development area of the lowest order level as a lower limit, and 1-2 grid units are arranged;
Dividing the faults of at least two different sequence levels in the longitudinal direction by utilizing a wavelet decomposition technology and a prediction error filtering analysis technology and combining the development positions of a reservoir to obtain the faults of at least two different sequence levels after division, wherein the sequence precision of the faults of at least two different sequence levels after division is higher than that of the faults of at least two different sequence levels;
establishing a first layer grid model based on the dividing parameters of the plane grid and the divided faults of at least two different orders;
And optimizing the first layer grid model according to a target multi-layer difference algorithm, and establishing a second layer grid model, wherein the second layer grid model has higher precision than the first layer grid model, and is a three-dimensional model of the thrust cladding structure belt structure.
2. The method of claim 1, wherein prior to said modeling a target construction from the morphology data and two-dimensional acoustic wave equation, the method further comprises:
Acquiring target survey data, the target survey data being geological data indicative of the thrust runner formations collected when surveyed;
and analyzing the target exploration data to obtain morphological data of the thrust covered structural band structure.
3. The method of claim 2, wherein the analyzing the target survey data to obtain morphology data of the thrust covered zone formations comprises:
and analyzing the target exploration data through a three-dimensional earthquake and well fine calibration technology, and acquiring morphological data of the thrust cladding structural band structure.
4. The method of claim 3, wherein the acquiring target survey data comprises:
Acquiring single well data of a target single well, wherein the target single well is a single well in a thrust cladding structural band;
analyzing the target exploration data through a three-dimensional earthquake and well fine calibration technology, and acquiring morphological data of the thrust covered zone structure, wherein the method comprises the following steps:
And processing the single well data through a wavelet decomposition technology to obtain the morphological data of the thrust cladding structural band, wherein the morphological data comprises gas reservoir ground data and fault parameters of the target single well.
5. The method of any one of claims 1 to 4, wherein optimizing the first mesh layer model according to a target multi-layer difference algorithm creates a second mesh layer model, comprising:
Optimizing the first layer grid model according to a target multi-layer difference algorithm to obtain an intermediate layer grid model;
and carrying out well layering data interpolation on the middle layer grid model to obtain the second layer grid model.
6. The method of claim 5, wherein the method further comprises:
and determining a target multi-level difference value algorithm from the candidate multi-level difference value algorithms, wherein the candidate multi-level difference value algorithm comprises at least two algorithms of a kriging algorithm, a minimum curvature method and a convergence method.
7. A modeling apparatus for a thrust cladding strip configuration, the apparatus comprising:
The first modeling module is used for building a target construction model according to morphological data and a two-dimensional acoustic wave equation, wherein the morphological data is used for indicating morphology and geographical position distribution of each stratum of the thrust cladding construction band construction;
the quantitative version acquisition module is used for developing forward modeling on the target construction model to acquire a target quantitative version, wherein the target quantitative version comprises at least two types of block construction patterns which are amplified n times, and n is greater than 1;
the second modeling module is used for quantitatively dividing the fault level of the target measuring plate and determining the fault combination relation of the thrust pushing covering structural band; analyzing the fault combination relation, and determining a section combination pattern of a fault in a complex structure band and a three-level fault mode, wherein the three-level fault mode comprises primary fracture, secondary fracture and three-level fracture, the primary fracture controls the development boundary of a fault block, the secondary fracture control area stretches, and the three-level fracture controls the complexity of the fault block; determining plane distribution characteristics and influence boundaries of faults of at least two different sequence levels according to the section combination patterns and the three-level fault modes, wherein the at least two different sequence levels comprise high-order faults including the primary fracture and the secondary fracture and low-order faults including the three-level fracture, the low-order faults are positioned at the tail ends of the high-order faults, the low-order faults are derivative faults, and the fault cuts and the connection of a plane grid are controlled by the high-order faults; determining dividing parameters of the plane grid by using an unstructured grid modeling technology according to the plane distribution characteristics and the influence boundary, wherein the scale of the plane grid takes a fault concentrated development area of the lowest order level as a lower limit, and 1-2 grid units are arranged; dividing the faults of at least two different sequence levels in the longitudinal direction by utilizing a wavelet decomposition technology and a prediction error filtering analysis technology and combining the development positions of a reservoir to obtain the faults of at least two different sequence levels after division, wherein the sequence precision of the faults of at least two different sequence levels after division is higher than that of the faults of at least two different sequence levels; establishing a first layer grid model based on the dividing parameters of the plane grid and the divided faults of at least two different orders;
And the third modeling module is used for optimizing the first layer grid model according to a target multi-layer difference value algorithm, and establishing a second layer grid model, wherein the second layer grid model has higher precision than the first layer grid model, and is a three-dimensional model of the thrust cladding structure belt structure.
8. A computing device comprising a processor and a memory having stored therein at least one instruction that is loaded and executed by the processor to implement the modeling method of a thrust covered zone construction of any of claims 1 to 6.
9. A computer readable storage medium having stored therein at least one instruction that is loaded and executed by a processor to implement a modeling method of a thrust clad build belt construction according to any one of claims 1 to 6.
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